Information for students, faculty and staff regarding COVID-19. (Updated: 21 October 2020)

Skip to content
printicon

Information, networks, and markets

  • Number of credits 7.5 Credits
  • Level Bachelor's level
  • Starting Autumn Term 2020

About the course

Content
The course introduces information theory, network theory and game theory to characterise and model systems that cannot be treated with the fully ordered or unordered interaction models of statistical physics. A perfect magnet or an ideal gas consists of indistinguishable parts that interact without intentions in completely ordered or disordered structures. Few interesting systems in nature can be described with such simple models. Social and economic systems often consist of unique elements that interact with specific intentions and exchange information in complex structures. But just as for simple systems such as magnets and gases, the key to understanding social and economic systems is to link microscopic descriptions with macroscopic phenomena.

By combining basic knowledge and understanding within information theory, network theory, and game theory, we derive simple models to understand the fundamental mechanisms of aggregate behaviour in markets. Starting with the concept of entropy, we derive basic concepts in information theory in order to mathematically describe the important role of information in social and economic systems. The network part of the course addresses crucial effects that arise because the interaction patterns are often neither fully ordered nor completely unordered. The game theory part deals with mathematics to describe situations when the outcome of interactions between different individuals depends on the intentions or strategies of each individual.

-How to play optimally given a specific odds?
-How can it pay-off to act unselfishly?
-How does the design of an auction affect the result?
-How does the position in a network influence strategies and outcomes in negotiation?

The course comprises a theory part of 5.0 credits and a project part of 2.5 credits.

Expected study results
To fulfil the goals of knowledge and understanding, the student should be able to:
  • describe and apply basic concepts, relationships and methods in information theory, such as the relationship between:
               - entropy and information,
               - entropy and the limit for maximum data compression,
               - data compression and optimal gaming,
  • describe and apply basic concepts and methods in network theory, such as:
               - strong and weak links, group structure and network dynamics,
               - network effects and information spreading on networks,
               - analysis and modelling of the structure of large-scale information networks,
  • describe and apply basic concepts and methods in game theory, such as:
               - simple games with and without interactions and the relationship between Nash and evolution equilibrium,
               - how rules, conventions and mechanisms of a market affect how individuals use and aggregate information,
               - how voting systems affect how individuals aggregate information and make a joint decision.

In order to fulfil the goals for proficiency and ability, the student should be able to:
  • demonstrate the ability to work towards a well-defined goal in a project using a project management model in groups of at least four people,
  • analyse a problem or system within one or more of the subject areas of information theory, network theory and game theory;
  • demonstrate the ability to collect, present and apply the necessary knowledge jointly in a group to solve the problem.

In order to fulfil the goals for values and critical approach, the student should be able to:
  • evaluate different solutions to problems in one or more of the subject areas of information theory, network theory and game theory;
  • reflect on their efforts in project work,
  • assess the quality of the group's results and give suggestions on how the results could be improved.

Forms of instruction
The teaching is conducted in the form of lectures, exercises, hand-in assignments and supervision in a larger project. Assignments and project work are compulsory elements of the course.


Examination
The examination of the course is in the form of oral and written reports of hand-in problems and a project, and an individual oral exam at the end of the course.


Eligibility
- A first programming course in either C or Python, in both cases including Matlab.
- A first course on statistics.
- Classical Mechanics.
Please also refer to the official "Required Knowledge".


Literature
Networks, crowds, and markets: reasoning about a highly connected world
Easley David., Kleinberg Jon.
New York : Cambridge University Press : 2010. : xv, 727 p. :
ISBN: 978-0-521-19533-1 (hardback)

Application and eligibility

Information, networks, and markets, 7.5 hp

Det finns inga tidigare terminer för kursen Autumn Term 2020 Det finns inga senare terminer för kursen

Starts

31 August 2020

Ends

1 November 2020

Study location

Umeå

Language

English

Type of studies

Daytime, 50%

Required Knowledge

First courses in programming, statistics, and classical mechanics are required.

Selection

Academic credits. Applicants in some programs at Umeå University have guaranteed admission to this course. The number of places for a single course may therefore be limited.

Application code

UMU-53013

Application

Application deadline was 15 April 2020. Please note: This second application round is intended only for EU/EEA/Swiss citizens. Submit a late application at Universityadmissions.se.

Application and Tuition fees

As a citizen of a country outside the European Union (EU), the European Economic Area (EEA) or Switzerland, you are required to pay application and tuition fees for studies at Umeå University.

Application fee

SEK900

Tuition fee, first instalment

SEK17,850

Total fee

SEK17,850

Contact us

Please be aware that the University is a public authority and that what you write here can be included in an official document. Therefore, be careful if you are writing about sensitive or personal matters in this contact form. If you have such an enquiry, please call us instead. All data will be treated in accordance with the General Data Protection Regulation.

Contact person for the course is:
Martin Rosvall